Weighted noise compensating method and camera used in millimeter wave imaging

ABSTRACT

Unpredictable response variations of the output value signals from radiometer or receiver channels due to noise are minimized when composing a millimeter wave image. The image is composed from composition signals which are each related to the corresponding output value signals from the channels. Some composition signals are weighted by a weighting factor which is different from a weighting factor used for weighting other composition signals. Preferably, the reciprocal of the standard deviation of variations of the output value signals from each channel is used as the weighting factor for deriving the composition signals from the output value signals from that channel. The intensity of each pixel of the image is composed by adding the weighted composition signals associated with that pixel.

CROSS-REFERENCE TO RELATED APPLICATION

This application is related to U.S. patent applications for an inventionfor an Offset Drift Compensating Flat Fielding Method and Camera Used inMillimeter Wave Imaging, Ser. No. (246.301), and for a BaselineCompensating Method and Camera Used in Millimeter Wave Imaging, Ser. No.(246.302), both filed concurrently herewith and assigned to the assigneeof the present application. The subject matter of these relatedapplications are incorporated herein by this reference.

FIELD OF THE INVENTION

This invention generally relates to millimeter wave imaging. Millimeterwave imaging involves creating an image of a scene from millimeterwavelength energy signals emanating from the scene. More particularly,the present invention relates to a new and improved method and camerawhich compensates for the random and unpredictable effects of noise inoutput value signals supplied by each of a plurality of radiometerchannels or receiver channels which receive and detect millimeterwavelength energy signals emanating from a scene. By compensating forthe random and unpredictable noise, the individual and particulardifferences in response of each channel are more accurately compensatedto improve the contrast and quality in an image composed by summing thecompensated output value signals from the channels.

BACKGROUND OF THE INVENTION

Millimeter waves are electromagnetic radiation characterized bywavelengths in the range of from 1 to 10 millimeters and havingcorresponding frequencies in the range of 300 GHz to 30 GHz. Millimeterwaves have the capability of passing through some types of objects whichwould stop or significantly attenuate the transmission ofelectromagnetic radiation of other wavelengths and frequencies. Forexample, millimeter waves pass through clothing with only moderateattenuation, pass through doors and walls, are capable of penetratingslight depths of soil, and are not obscured or adversely influenced byfog, cloud cover and some other types of visually-obscuringmeteorological conditions. Because of these properties, millimeter waveimaging has been employed to detect contraband and weapons concealedbeneath clothing of an individual, to alert law enforcement authoritiesof the location of individuals and objects within the interior of a roomor building prior to executing search warrant raids, to detect thepresence and location of buried land mines, and for landing and takeoffguidance for aircraft when meteorological conditions obscure runways,among many other things.

According to known laws of physics, the amount or intensity ofelectromagnetic energy emitted by an object is proportional to itsphysical temperature measured in degrees Kelvin. The radiationoriginates from thermally-induced charged-particle accelerations,subatomic particle interactions and other quantum effects. These quantumeffects account for a distribution of radiation throughout a broadspectrum of frequencies, as recognized by Planck's Law. Consequently, itis typical to characterize the amount of energy emanating from a pointor object in a scene by its apparent brightness temperature.

The energy emanating from a point or object in the scene results fromemission and reflection. Emission and reflection are related to oneanother such that highly emissive objects are only slightly reflective,and highly reflective objects are only slightly emissive. Passivemillimeter wave imaging creates an image from both the emitted and thereflected electromagnetic energy. Active millimeter wave imaging alsorelies on energy emission and reflection, but enhances the energycontent in a scene by illuminating the scene with added energy. Theadded energy increases the contrast or distinction in energy emanatedfrom different points within the scene, primarily by increasing thereflected energy. Because passive millimeter wave imaging relies on theinherent natural energy emanating from the objects and the background inthe scene, and such inherent natural energy is generally less than theamount of energy resulting from actively illuminating the scene withadded energy, it is typically more difficult to create an imagepassively.

In some scenes, the distinction between the brightness temperature of anobject and the brightness temperature of the background is relativelysmall. Slight differences in the brightness temperature of the objectsand the background increase the difficulty of detecting those energydifferences with enough distinction to create images with good contrastand resolution relative to the background. Inadequate contrast,resulting from an inability to detect relatively small differences inradiated energy from point to point within the scene, degrades thequality of the image. The ability to form good millimeter wave images istherefore directly related to the ability to recognize relatively smalldifferences in the amount of millimeter wave energy emanated fromdifferent points within the scene, which is particularly important inpassive millimeter wave imaging because of the relatively smalldifferences in energy emanated from objects in the scene.

Millimeter wave imaging is further complicated by the fact thatmillimeter wave energy constitutes only a very small band or part of thespectrum of energy emitted by a body. The temperature-related quantumeffects result in an energy distribution throughout a wide spectrum offrequencies. For millimeter wave imaging, only the frequency spectrum ofradiation within the millimeter wavelength (30-300 GHz) is examined.Moreover, the typical millimeter wavelength frequency band used inmillimeter wave imaging is even further restricted, for example, at 94±2GHz. The amount of energy available is generally related to thebandwidth. Consequently, the limited bandwidth also reduces the amountof energy available to be detected for use in creating millimeterwavelength images.

Further complications arise from the noise-like origin of the millimeterwavelength energy which is detected to create the images. The thermallyinduced quantum effects result in a significant variations in frequencydistribution and intensity of the emitted energy, thereby causing theradiated energy to have random characteristics similar to noise. In theusual sense, noise is considered as a factor which contaminates orderogates an otherwise pure signal. The relatively pure nature of theunderlying signal assists in distinguishing the corrupting noise andeliminating its effects, in typical signal processing. However, there isno underlying pure signal in passive millimeter wave imaging, due to thethermally induced and random quantum effects which create the emittedradiation. Consequently, it is necessary to rely on a primary noise-likesignal for the information to create the image, and to attempt toeliminate or reduce the effects of other noise-like signals that havethe potential to obscure the desired information from a primary signal.Thus, distinguishing the desired information carried by a noise-likesignal from spurious and derogating noise-like signals of similarcharacteristics is a significant challenge in millimeter wave imaging.

The noise-like origin and characteristics of natural millimeter waveradiation, the limited bandwidth of energy within the millimeterwavelength spectrum from which to form the image, the relatively smalldifferences in brightness temperature of the object in a scene comparedto its background, and many other factors, have indicated a capabilityto enhance millimeter wave imaging by using multiple channels(radiometer channels are typically used for passive imaging and receiverchannels are typically used for radar and most types of active imaging,although radiometer channels may be used in certain instances fornon-radar active imaging), arranged in a focal plane array and scanningthe energy emanating from the scene into the multiple channels. Thechannels convert the received or scanned-in radiant energy intoelectrical output value signals or samples. The multiple output valuesor samples from multiple different channels scanning each point areadded together to create a pixel in the image which corresponds to thatpoint in the scene. Each pixel has an intensity which is derived fromadding the multiple samples.

One disadvantage of using multiple radiometer channels or receiverchannels to obtain the multiple samples to be added together is thateach channel has its own individual and particular responsecharacteristics. In response to viewing exactly the same point havingone brightness temperature, each channel creates a slightly differentoutput value. When the slightly different samples from the multiplechannels are combined to create each pixel, the intensity of the pixeldoes not faithfully represent the brightness temperature of thecorresponding point in the scene. Adding signals which are slightlydifferent, even when those signals originate from a single point in thescene with a uniform brightness temperature, results in slightderogation in contrast of the image. Such image derogation is notrelated to the energy content of the scene, but is related to theslightly different characteristics of the channels used to obtain thesamples. Moreover because of the scanning effect, the anomalous effectsintroduced by the individual and different characteristics of eachchannel are distributed among various different pixels in the image,thereby decreasing the contrast and the quality of the image.

Despite careful efforts to make each radiometer and receiver channelexactly the same, each channel has its own unique gain, offset and noisetemperature and response characteristics. Gain refers to the capabilityof the channel to amplify input signals it receives. Each channelcharacteristically amplifies a known constant input signal by a slightlydifferent amount. Offset refers to a characteristic output signal levelof the channel in response to a known input signal. The output signallevel from each channel will be slightly different in magnitude inresponse to a known uniform input signal. The noise temperaturecharacteristics of a channel relate primarily to electricalimperfections of components used in the channel, as opposed to thephysical temperature of the channel itself. The noise temperature isextremely high relative to physical thermal temperature, and eachchannel has a significantly different noise temperature even when thephysical temperature of the channels is maintained uniform.

To counteract the effects of the individual response characteristics ofeach channel, it is traditional to position a mechanical chopper in theoptical path between the scene energy and the channels. The chopperperiodically and rapidly introduces a known uniform brightness element,such as a black body, into the optical path, and each channel is quicklyreadjusted while the uniform brightness element is momentarily insertedin its optical path. The use of such choppers, and the necessity toquickly readjust each channel while still measuring radiation from thescene, greatly complicates the imaging process and the equipmentnecessary to perform the imaging.

To avoid the use of choppers, efforts have been made in the past tonormalize the gain response characteristics of each channel.Normalization involves dividing the output response of each channel bythe gain of the channel. In this manner, the response of each channel isgain normalized, so that when the samples from the channels are added,their contributions are of uniform relativity based on gain. While gainnormalization has enhanced the quality of the image, gain normalizationhas not eliminated image anomalies arising because of the particulardifferences in offset and noise temperature characteristics of thechannels. Moreover, the typical type of gain normalization employed inthe prior art has been discovered not to account adequately for allvariations in gain among the different channels.

SUMMARY OF THE INVENTION

The present invention involves a new and improved method of reducing oreliminating the effects of the random and inherent noise-responsivevariations in output value signals from radiometer channels or receiverchannels into which radiant energy from a scene is directed by a movablescanning element during millimeter wave imaging. While efforts have beenmade in the past to compensate for differences in gain among thechannels when composing the millimeter wave image, it is believed thatno efforts have been made to reduce the unpredictable and non-calculablevariations in output value signals resulting from differences inresponse characteristics due to random noise. As a consequence of thesepast practices, the contrast and quality of the millimeter wave imageshas been diminished.

In general, the present invention involves compensating for the inherentand unpredictable variation in response to noise of the output valuesignals from each of a plurality of channels receiving radiant energyemanating from a scene, in the context of millimeter wave imaging. Amethod of the invention involves composing an image of the scene from aplurality of composition signals which are each related to correspondingoutput value signals from the channels, weighting at least some of thecomposition signals by a weighting factor, and using a weighting factorfor weighting at least some of the composition signals which isdifferent from a weighting factor used for weighting at least some ofthe other composition signals, before composing the image from theplurality of weighted composition signals. Preferably, the standarddeviation of variation of each output value signal relative to thatsignal's mean output value is established, and each composition signalis weighted by multiplying the corresponding output value signal by thereciprocal of the standard deviation of that output value signal. Theimage is thereafter composed by adding the weighted composition signals.The image is preferably formed by a plurality of pixels, and theintensity of each of the pixels is established by adding the weightedcomposition signals attributable to that pixel.

Weighting the composition signals based on the standard deviation ofvariation of each of their corresponding output value signals has theeffect of minimizing the variance of the composition signals when theyare added together to form the image and the intensity of each pixel ofthe image. By minimizing the variance of the added-together compositionsignals, the anomalous effects created in the image as a result of therandom and unpredictable noise response characteristics of each channelis minimized, resulting in greater contrast and quality in the imageproduced.

Such improvements are particularly useful in forming the intensity ofeach pixel of the image from multiple output value signals from multiplechannels. In such circumstances, weighting the contributions from eachchannel in a relationship which is inversely related to the standarddeviation of the channel contributing to the pixel intensity assuresthat those channels that are more noisy will have less contribution tothe final pixel intensity than the contributions from those channelswhich are less noisy. Reducing the contribution of the channels whichare more noisy and increasing the contribution of the channels which areless noisy has the effect of diminishing anomalous effects in the imagewhich would otherwise occur because of the random and unpredictableeffects of noise. Moreover, the present improvements can be used inconjunction with other techniques to improve image quality withoutreducing the benefits obtained from the present invention.

Other preferable aspects involve measuring the variation in response ofthe output value signals from each channel to establish the weightingfactor for each channel. Since the random noise-created effects whichthe present improvement is intended to minimize can not be calculated,the response of the channels to radiant energy from points of uniformbrightness within a scene provides the basis for determining thedeviation information from which the weighting factor is obtained foreach channel.

Other preferable aspects involve reducing a scene-independent baselinesignal component of the output value signal from each channel. Themagnitude of the baseline signal is established at each position of amovable scanning element which directs radiant energy from the sceneinto the channels. The magnitude of the baseline signal at each positionof the movable scanning element is subtracted from the output valuesignal. Subtracting the value of the baseline signal results in abaseline-compensated output value signal which more clearly representsthe brightness temperatures of points in the scene in a manner which hasnot been influenced by the scene-independent effects of the movablescanning element. The magnitude of the baseline signal is also obtainedby measuring the output value signals from each channel at each positionof the movable scanning element while energy from a scene of uniformbrightness is directed into each channel.

A further preferable improvement in composing the image involvesnormalizing the weighted baseline-compensated output signals from eachchannel on the basis of a flat fielding response of the channels. Thenormalization involves compensating for the different gains of eachchannel and the different drifts in offsets of the output value signalsfrom each channel. The gain characteristics of each channel arepreferably measured, while the different offset characteristics of eachchannel are preferably calculated based on a consistency condition thatan unknown mean scan temperature encountered by each channel into whichradiant energy from a portion of the scene is scanned is equal to theaverage of the intensities of those pixels to which thebaseline-compensated output signals from that channel contributes, wherethe average of pixel intensities is calculated based on an expressionfor the average pixel intensities in terms of the unknown mean scantemperatures of the channels. The basis for the normalizationcalculation is that each channel observes a different mean scanbrightness temperature from a portion of the scene from which radiantenergy is directed to the channel in comparison to the mean brightnesstemperature of the entire scene.

Another aspect of the present invention pertains to a millimeter waveimaging camera implementing the methodology described above. Themillimeter wave imaging camera comprises a signal processor forperforming the actions and calculations to weight the value of eachcomposition signal, to subtract the baseline signal component from theoutput value signals to establish the baseline-compensated componentsignals, to weight the value of each baseline-compensated componentsignal, to normalize the baseline-compensated weighted compositionsignals, and to compose the intensity of each pixel of the image byadding the values of the normalized, baseline-compensated and weightedsignals.

A more complete appreciation of the scope of the present invention andthe manner in which it achieves the above-noted and other improvementscan be obtained by reference to the following detailed description ofpresently preferred embodiments taken in connection with theaccompanying drawings, which are briefly summarized below, and byreference to the appended claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block and schematic diagram of a millimeter wave imagingcamera which incorporates and illustrates features of the presentinvention.

FIG. 2 is a partial perspective view of a number of individualradiometer or receiver channels of a focal plane array in the camerashown in FIG. 1.

FIG. 3 is an electrical component block diagram of a single radiometerchannel, of the type which might be used as one of the channels of thefocal plane array shown in FIGS. 1 and 2.

FIG. 4 illustrates five separate scanning paths of five separatechannels created by a movable scanning element of the camera shown inFIG. 1.

FIG. 5 is a more complete version of FIG. 4, illustrating theoverlapping nature of the scanning paths of sixty-four separate channelsof a focal plane array.

FIG. 6 is a flow chart of the actions and computations performed by thecamera shown in FIG. 1 to compose an image in accordance with themethodology of various aspects of the present invention.

TERMINOLOGY

In the following Detailed Description, certain nomenclature and symbolsare used to describe the present invention. Although the terms are alsodescribed in the Detailed Description, the following list presents manyof those terms for reference purposes. Symbol Definition A The N × Nmatrix used in the derivation of the solution for the θ_(i). A_(i) Thei^(th) column vector of matrix A. A′ The N × (N − 1) matrix that resultsfrom deleting the N^(th) column vector of matrix A. (A′)_(inv) The (N− 1) × N matrix used in computing θ_(i). b The N × 1 column vector usedin computing θ_(i). B_(ik) The baseline signal of channel number i atobservation position k. (1 ≦ i ≦ N, 1 ≦ k ≦ L) β The pre-detectionbandwidth of a channel. C(m) The contribution counts to each pixel m inthe composed image for 1 ≦ m ≦ M. g_(i) The gain or amplification ofchannel number i. (1 ≦ i ≦ N) i The designation of one channel in thefocal plane array. I(m) The image intensity at pixel number m of thedisplay. (1 ≦ m ≦ M) I′(m) The image intensity at pixel number m of thedisplay of an intermediate image formed during the composition of afinal image using a drift compensated flat fielding technique describedbelow. k The observation position of the movable scanning element, suchas the wedge shaped element, where an observation of the output valuesignals from each channel of the focal plane array is sampled. L Thenumber of observation positions of the movable scanning element where achannel output value signal or observation is sampled or obtained. Also,the number of subframes used to form a complete image of the scene, witheach subframe containing N number of channel output value signals u ateach observation position. M The selected maximum number of pixels whichconstitute the display. m The designation for each pixel of the displaywhich contributes to the image composed. n The number of a scan number.N The number of channels in the focal plane array. Also, the number ofsimultaneous linear equations expressing relationships between theunknown mean relative scan brightness temperatures θ₁, θ₂, . . . ,θ_(N). u The uncompensated output value signal from a channel, each alsoreferred to as an observation. s_(i) The scene brightness temperatureencountered by channel i. T_(i) ^(R) The noise temperature for channeli. u_(i) The uncompensated output value signal u from a channel i.u_(ik) (n) The uncompensated output value signal u from a channel i atrotational position k in scan number n. v The number of complete scans(e.g., revolutions for the rotating wedge shaped element) which createssufficient data for forming values of the baseline signalcharacteristics for each channel. u_(o,i) The offset value of channel i.x_(ik) The channel output value signal or observation sampled orobtained from the channel i at observation position k, after baselinesubtraction. (1 ≦ i ≦ N, 1 ≦ k ≦ L) {circumflex over (x)}_(ik) Thechannel output value signal or observation x_(ik) from the channel i ofthe focal plane array at the observation position k of the movablescanning element after normalization using a flat fielding technique. (1≦ i ≦ N, 1 ≦ k ≦ L) {overscore (x)}_(i)${The}\quad{average}{\quad\quad}\frac{1}{L}\underset{l = 1}{\overset{L}{\sum\quad}}x_{il}\quad{of}\quad{the}\quad{output}\quad{value}\quad{signals}\quad{or}\quad{observations}$from channel i over one complete scan (all L observation positions) bythe movable scanning element. (1 ≦ i ≦ N) σ The standard deviation ofthe random noise signal produced by the channel number i, (1 ≦ i ≦ N),when that channel views a scene of constant brightness temperature.{circumflex over (σ)}_(i) The standard deviation of the normalizedversion of the random noise signal produced by the channel number i, (1≦ i ≦ N), when that channel views a scene of constant brightnesstemperature. σ_(i) ^(V) The standard deviation of the output valuesignal of the channel i when viewing a general scene i.e. a scene withan arbitrary brightness temperature distribution. σ^(Backend) Thebackend noise standard deviation of a channel. τ The time constantassociated with a post-detection bandwidth of a channel. θ_(i) The meanrelative scan brightness temperature seen by each channel i, (1 ≦ i ≦ N)in the course of a complete scan. δ_(ikm) The binary quantity that hasvalue 1 if the output value signal from channel i at observationposition k contributes to pixel number m, and it has the value 0otherwise. δ_(ikm) specifies the scanning pattern or scanning trajectoryof each channel of the focal plane array, and are known quantities foreach channel for 1 ≦ i ≦ N, 1 ≦ k ≦ L, and 1 ≦ m ≦ M.

DETAILED DESCRIPTION

A camera 10, shown in FIG. 1, incorporates and operates in accordancewith the various aspects of the present invention. The camera 10includes a movable scanning element 12 which receives emitted andreflected radiation energy emanated from a scene 14. The scene 14 isformed by points 16, and each of the points 16 is either part of anobject 18 within the scene 14 or part of a background 20 within thescene 14. The points 16 of the scene 14 emanate radiation energy with anintensity which is related to the brightness temperature of that point.The emanated radiation energy includes energy in a millimeter wavelengthfrequency band which is emitted and reflected from the objects 18 andthe background 20.

The movable scanning element 12 receives emanated energy from the scene14, and directs or steers that energy through an optical element 22 to afocal plane array 24 of channels 26. Each channel 26 will typically be aradiometer channel when the camera 10 is used in passive imaging, andeach channel 26 will typically be a receiver channel when the camera 10is used in active imaging, although it may be possible that either typeof channel may be used for either type of imaging. The individualchannels 26 of the focal plane array 24 are shown in FIG. 2 and anexemplary radiometer channel 26′ is shown in FIG. 3. As shown in FIG. 1,an optical path 28 extends from the scene 14, through the movablescanning element 12, to the optical element 22 and to the focal planearray 24.

As shown in FIG. 2, the focal plane array 24 is formed by a multiplicityof individual channels 26, arranged in a two-dimensional array toreceive radiation energy. Each channel 26 responds to energy received byan antenna 30 of each channel 26, as is also shown in FIG. 3. Eachantenna 30 preferably takes the form of a conventional endfire travelingwave slot antenna. Each antenna 30 is preferably formed by two metallicelements 32 and 34 that remain on a dielectric support substrate 36after sheet metal (not shown) which was originally attached to thesubstrate 36 has been photolithographically etched away to leave theremaining elements 32 and 34. In this manner, a plurality of channels 26can be formed in parallel on a single support substrate 36, and thefocal plane array 24 may be formed by stacking or positioning a numberof the support substrates 36, each with a plurality of parallel channels26, in parallel adjoining relationship with one another, as shown inFIG. 2.

The shape of the metallic elements 32 and 34 establishes a cavity 38into which the radiation from the scene 14 (FIG. 1) is received. Eachchannel 26 establishes an output value signal based on the amount ofradiation received by the antenna 30. The shape of the cavity 38establishes a field of view for each channel 26. The field of view isthat angular spatial volume from which radiation energy is received bythe antenna 30. The inherent field of view of each antenna 30 is definedby a relatively slight angle of divergence relative an axis (not shown)between symmetrical parts of the cavity 36 and parallel to the metallicelements 32 and 34.

The inherent field of view of each channel 26 causes the vast majorityof radiation energy to be received within the relatively slight angle ofthe field of view of each antenna 30. Because the natural field of viewof each antenna 30 is limited in this manner, the natural field of viewof each channel 26 is not usually sufficient to receive energy from theentire scene 14 (FIG. 1), even when multiple channels 26 are employed inthe array 24 of the camera 10. Consequently, the movable scanningelement 12, shown in FIG. 1, is employed in the camera for the purposeof increasing the field of view of the optical path 28 so that radiationenergy from the entire scene is scanned, directed or steered into thefocal plane array 24.

The movable scanning element 12 directs or scans emanated radiationenergy from all points 16 of the scene 14 into the focal plane array 24,so that the emanated radiation energy from the entire scene 14 isdetected and used to create an image. Of course, if the focal planearray 24 had enough channels positioned at the appropriate locations sothat the inherent field of view of each antenna of each channel receivedenergy from the entire scene 14, and there was some amount of overlapbetween the fields of view inherently obtained from the antennas of thechannels, it would not be necessary to use the movable scanning element12. However because of practical size and cost considerations, themovable scanning element 12 will typically be employed in the camera 10.

One type of movable scanning element 12 employs a wedge shapedrefractive element 40 which is rotated about an axis 42. The wedgeshaped characteristic of the element 40 increases the field of view ofthe optical path 28 by refracting the energy from a wider field of view.Consequently, energy from all points 16 within the scene is scanned intoone or more of the channels 26 of the focal plane array 24. The increasein the field of view achieved by the scanning element 12 results becauseof the refraction characteristics of the wedge shaped element 40, and byrotation of the wedge shaped element 40 around the axis 42.

The rotation of the wedge shaped element 40 creates a scanning path ortrajectory in the form of a circle, as shown in FIG. 4. Five circles 44,46, 48, 50 and 52 are illustrated in FIG. 4, and each circle 44, 46, 48,50 and 52 illustrates the scanning path or trajectory of points 16 inthe scene 14 from which five separate channels 26 of the focal planearray 24 (FIGS. 1 and 2) receive radiation energy emanated from thescene 14. One channel of the focal plane array receives radiation energyemanated from those points 16 of the scene 14 which are illustrated by asingle circle. Some of the circles 44, 46, 48, 50 and 52 shown in FIG. 4overlap with one another, indicating that different channels receiveenergy emanated from the same points within the scene 14 where theoverlap occurs.

FIG. 5 illustrates the overlapping nature of all of the fields of viewof sixty-four circles created by sixty-four channels of a practicallysized focal plane array. The overlapping nature of all of the fields ofview shown in FIG. 5 is the same functionally as the fewer number offields of view shown more simplistically in FIG. 4.

As is apparent from the overlapping scan patterns shown in FIGS. 4 and5, each channel receives radiation emanating from many points in thescene 14 but none of the channels receive radiation emanated from all ofthe points in the scene. The non-overlapping nature of some of thescanning patterns shown by the circles 44, 46, 48 and 50 in FIG. 4illustrates that some channels receive radiation that other channels inthe focal plane array do not receive, and the fact that none of thescanning patterns encompass the entire scene 14 illustrates that none ofthe channels receive radiation from all points in the scene.

The output value signals for each channel are electrical signals derivedby interaction of conventional components of each channel 26. Theconventional components of a radiometer channel 26′ are shown in FIG. 3.The characteristics of the cavity 38 of the antenna 30 cause theradiation energy at a desired millimeter wavelength to set up atraveling wave within the cavity 38. The radiation energy at the desiredmillimeter wavelength has the effect of developing a relatively smallelectrical signal between the two elements 32 and 34, and this signalrepresents the strength of the radiated energy at the desired millimeterwavelength frequency. The signal from the antenna elements 32 and 34 isamplified by a low noise amplifier 54 and the amplified signal isapplied to a mixer 56.

In the mixer 56, the output signal from the low noise amplifier 54 isheterodyned with a signal from a subharmonic local oscillator 58. Theresult of the heterodyning in the mixer 56 is an output signal from themixer 56 which is reduced in frequency relative to the desiredmillimeter wavelength frequency to which the antenna 30 responds, butwhich retains the energy content information of the millimeterwavelength signal received by the radiometer channel 26′.

The reduced frequency signal from the mixer 56 is applied to anotheramplifier 60 which amplifies its magnitude before supplying theamplified signal to a detector 62. The detector 62 recognizes the valueof the energy content of the signal supplied to it and supplies anoutput signal related to the energy content to another amplifier 64. Theamplifier 64 further amplifies the level of the signal from the detector62 and supplies the amplified signal to a sample and hold circuit 66.The signal supplied to the sample and hold circuit 66 thereforerepresents the amount of energy at the desired millimeter wavelengthfrequency which the radiometer channel 26′ detects.

The sample and hold circuit 66 responds to a control signal 68 toestablish the time at which the energy content-related signal from theamplifier 64 is to be sampled and held. In response to the controlsignal 68, the sample and hold circuit determines the value of theenergy content-related signal supplied to it from the amplifier 64, andholds that sample value until the next subsequent control signal 68causes it to sample another instantaneous value of the signal suppliedby the amplifier 64 at that later time.

The sample signal which is held and supplied by the sample and holdcircuit 66 is an output value signal 70. The output value signal 70represents the quantity of millimeter wave radiation within a relativelynarrow frequency band surrounding a frequency equal to two times thelocal oscillator frequency, as detected by the radiometer channel 26′ atapproximately the time of the control signal 68.

The output value signal 70 from the sample and hold circuit 66 isapplied to a multiplexer 72. The multiplexer 72 may be common to amultiplicity of radiometer channels 26′, such as all of the radiometerchannels 26′ attached to a single dielectric substrate 36 (FIG. 2).Alternatively, the multiplexer 72 may be common to all of the channelsof the entire focal plane array 24 (FIGS. 1 and 2). The multiplexer 72selects the desired output value signal 70 from each of the radiometerchannels 26′ in response to a select signal 74, and the selectedradiometer output value signal 70 is thereafter supplied from themultiplexer 72 to a signal processor 76 of the camera 10 (FIG. 1). Thesignal processor 76 uses the output value signals 70 from the radiometerchannels 26 to formulate or compose an image 78 (FIG. 1) whichcorresponds to the scene 14. The signal processor 76 preferably includesa conventional digital computer which has been programmed to perform theactions and to execute the computations described herein.

Although not specifically shown, a receiver channel is generally similarto the radiometer channel 26′ shown in FIG. 3, except that in place ofthe detector 62 a conventional magnitude and phase detector component isemployed. The conventional magnitude and phase detector componentrecognizes phase information between the illuminating signal and thereceived signal, as well as the magnitude of the energy content at theparticular phase relationship. The magnitude and phase information issampled and held by the circuit 66 in response to the control signal 68,and the multiplexer 72 delivers the signals containing the magnitude andphase information to the signal processor 76 (FIG. 1). The additionalphase relationship information allows the signal processor 76 (FIG. 1)to derive additional knowledge describing the scene, such the range andthe velocity of points within the scene.

It is also typical in a receiver channel (not shown) that the componentdesignated as the local oscillator 58 in FIG. 3 also performs the roleof generating the energy use to illuminate the scene, as well as aheterodyning function. In such circumstances a conventional beamsplitting device is used to direct part of the illuminating energy outof the antenna 30 and to allow energy received from the scene to betransferred through the other components of the receiver channel tofunction in the manner described. Under such circumstances, a signaldescribing the illuminating signal is supplied to the magnitude andphase detection component which replaces the detector 62, so that thephase information can be derived as well as the magnitude information.

As shown in FIG. 1, the signal processor 76 receives position signals 80from a position sensor 82 which is associated with the movable scanningelement 12. The position sensor 82 derives signals corresponding to eachof the scanning or rotational positions of the wedge shaped element 40.One technique for deriving the position signals is to attach a bar codeto the exterior of the rotating wedge shaped element 40, and to read thebar code directly to obtain rotational position information at eachrotational interval of the wedge shaped element 40. The information fromthe position signals 80 correlates to points 16 in each scanningtrajectory of the scene 14, represented by the circles 44-52 (FIG. 4),for each channel 26 of the focal plane array 24.

The position signals 80 are also used by the signal processor 76 tocoordinate the delivery of the control signals 68 to the sample and holdcircuit 66 (FIG. 3). In response to the control signals 68, the outputvalue signals 70 from each channel 26 are derived at points 16 in thescene 14 which correlate to the position signals 80. Consequently, eachoutput value signal 70 from each channel 26 is established andcorrelated to a point 16 in the scene 14 by the position signals 80 andby the delivery of the control signals 68 and the select signals 74(FIG. 3) in relation to the position signals 80.

The signal processor 76 associates the output value signals 70 frompoints 16 in the scene 14 with individual pixels 84 of a display 86 inaccordance with the position signals 80. An image 78 is formed on thedisplay 86, and the image 78 is formed by individually controlling theintensity of each of the pixels 84. The image 78 formed on the display86 includes a representation of the scene 14, as well as the object 18in the scene and the background 20 of the scene.

To form the image 78, the signal processor 76 correlates each outputvalue signal 70 from each channel 26 at each position of its scanningpath, as determined by the position signals 80, with an individual pixel84 of the display 86. The signal processor 76 calculates the intensityof each pixel 84 from a sum of the output value signals 70 associatedand correlated with each individual pixel 84, after the output valuesignals 70 have been processed in accordance with the variousimprovements described below. The final intensity of the each pixel 84is dependent on the contribution from each of the output value signals70 from each channel which scans the point 16 in the scene 14 thatcorresponds to the pixel 84 in the image 78.

The correlation of the contributions from the output value signals 70 toeach pixel 84 in the image 78 is facilitated by generating a table thatcorrelates each specific position signal 80 with each channel 26 thatcontributes an output value signal to each pixel 84. Such correlation isillustrated by a pixel position table shown below. The pixel positiontable illustrates the form of entries for a focal plane array 24 with Nchannels and a wedge shaped element 40 with L discrete position marks onits periphery, each of which generates a separate position signal 80.Each entry in the pixel position table relates to a pixel number lyingbetween 1 and M, where M is the number of pixels in the full image 78.Computing this table before performing imaging computations, and storingthe table in memory for later access when performing the imagingcomputations, is of benefit when composing the full image 78 from thechannel output value signals 70 recorded at each position represented bya position signal 80. Channel 1 Channel 2 . . . Channel N Position 1Pixel Number Pixel Number . . . Pixel Number Position 2 Pixel NumberPixel Number . . . Pixel Number . . . . . . . . . . . . Position L PixelNumber Pixel Number . . . Pixel Number

Although the movable scanning element 12 has been described inconjunction with a rotating wedge shaped element 40, other types ofmovable scanning elements may be used. For example, another type ofmovable scanning element is a rotating mirror located in the opticalpath which is retained at a non-orthogonal angle to its rotational axis.The non-orthogonal orientation causes reflections of the radiated energyalong a path that is not parallel to the rotational axis, in a mannerwhich is functionally the same as creating the scanning path ortrajectory achieved by the rotating wedge shaped element 40.

The scanning trajectory or path created by the rotating wedge shapedelement 40 is illustrated as circular in FIGS. 4 and 5, but the scanningpath need not be circular. A variety of different scanning paths may beemployed depending upon the geometry and orientation of the focal planearray and the scene which is to be scanned. For example, linear scansmay be used in certain circumstances. A linear scanning path can beachieved by using two counter-rotating wedge shaped elements 40 in theoptical path. Any scanning path which involves scanning the scene 14with non-zero overlaps between the scanning paths of the individualchannels 26 may be used.

In general, a single complete scan of the radiation energy emanatingfrom the scene 14 may be used to create a single image 78 on the display86. By updating the image 78 with periodically-executed scans of thescene 14, the images 78 may be presented on the display 86 in arelatively time-current and time-updated manner.

One aspect of the present improvements has resulted from the discoverythat, when the wedge shaped element 40 is rotating and scanning a sceneof a uniform brightness temperature, i.e. a flat field, the output valuesignal 70 for each channel 26 of the focal plane array 24 is dependenton the position of the wedge shaped element 40. This discovery has ledto the realization that output value signals of the channels becomepartially independent of the brightness temperature of the points 16 inthe scene 14. The scene-independent portions of the channel output valuesignals which occur as the wedge shaped element 40 accomplishes a fullscan of uniform field scene 14 are described herein as a baseline signalor curve for that channel. The strength of the baseline signal isdependent upon the position of the wedge shaped element 40. Moreimportantly however, the value of the baseline signal may overwhelm thechange in channel output value signals that occurs in response tobrightness temperature contrasts in a typical scene 14. Consequently,the effect of the baseline signal may eliminate or reduce contrasts inbrightness temperature when scanning the scene.

While the exact cause of the baseline signal may not be fullyunderstood, it is believed that the baseline signal is the result of astanding wave which occurs between the antenna 30 (FIGS. 2 and 3) ofeach channel 26 and the refractive surfaces of the rotating wedge shapedelement 40. Because of the angled surface of the wedge shaped element40, the distance between the antenna 30 and the refractive surfaces ofthe wedge shaped element 40 varies in direct relationship to therotational position of the wedge shaped element. This change in distanceor geometry has the effect of changing the phase or reflectioncharacteristics which a standing wave would undergo between the wedgeshaped element 40 and the antenna 30, at different positions of thewedge shaped element 40. This being the case, other types of movablescanning elements 12, such as a mirror with a non-orthogonally orientedrotational axis, is also likely to create standing waves andscene-independent variations in the output value signals from thechannels.

The changing characteristics of the standing wave at different positionsof the wedge shaped element 40 causes the magnitude of the output valuesignal 70 from each channel to be altered in a manner related to thechanging values or strengths of the standing wave. The output valuesignals 70 from each channel are thereby varied by an influence which isentirely independent of the radiation emanating from the scene. Thechange in value of the output signal resulting from this effect isundesired because it is interpreted as a change in emanated radiationfrom the scene, and therefore adversely influences the composition orformation of the image 78 on the display 86.

It has been discovered that the shape or curve of the baseline signalsis substantially stable from one complete rotation of the wedge shapedelement to the next, and the characteristics of the baseline signalcurve are repeatable during each revolution of the wedge shaped elementover relatively long periods of time. The dependence of the magnitude ofthe baseline signal of each channel on the rotational position of thewedge shaped element 40, and the substantial consistency of thisbaseline signal over relatively long periods of time, permits thebaseline signal to be identified and valued, and then subtracted fromthe output value signals from the channels derived at correspondingrotational positions of the wedge shaped element. Subtracting the valueof the baseline signal from the output value signals of the channels ateach position of the wedge shaped element has the effect of eliminatingthe scene-independent influences on the channel output value signals,permitting values to be obtained which truly relate to the brightnesstemperatures of the points 16 of the scene 14.

Formulating the value of the baseline signal involves recording theoutput value signals from each channel over a selected number v ofconsecutive revolutions of the wedge shaped element while scanning ascene having a flat field of uniform brightness points. Averaging theoutput value signals at each position over the selected number ofconsecutive revolutions yields a curve of baseline signals with anynoise related variation suppressed for each channel.

The computation of the baseline signals for each channel is as follows.The output value signal u (70) from each channel i at rotationalposition k of the wedge shaped element in scan number n is denoted byu_(ik) (n). The dependence on scan number n is equivalent to adependence on time. The estimated baseline values B_(ik) for eachchannel at the positions are set forth by Equation (1): $\begin{matrix}{{B_{ik} = {\frac{1}{v}{\sum\limits_{n = 1}^{v}\quad{x_{ik}(n)}}}},{1 \leq i \leq N},{1 \leq k \leq L}} & (1)\end{matrix}$In Equation (1), N is the number of channels, and L is the number ofrotational positions of the wedge shaped element 40. It has been foundthat the use of v=100 revolutions creates sufficient data for formingvalues of the baseline signal characteristics for each channel.

Once the baseline curve for each channel has been developed, thecorrection of the output value signals 70 for each channel is performedby subtracting the baseline values from the observed output valuesignals. Subtraction yields the signal x_(ik) that is substantially freefrom the scene-independent and undesired effects of rotational positionof the wedge shaped element, as shown by Equation (2):x _(ik)(n)=u _(ik)(n)−B _(ik),1 ≦i≦N, 1≦k≦L.   (2)In Equation (2), the value of the baseline curve for each channel i atthe position k is represented by the value B_(ik).

By identifying and measuring the value of the baseline curve for eachchannel at each position of the wedge shaped scanning element 40, andthereafter subtracting the value of the baseline curve from the outputvalue signals from each channel at each position, the signals used bythe signal processor 76 in creating the image 78 represent thedifferences and contrasts in the brightness temperature of the points 16within the scene 14. Consequently, the image 78 is more accurate sinceit is no longer adversely influenced by the scene-independentinfluences.

The baseline-subtracted channel samples or observations x_(ik) are usedto create a set of new values {circumflex over (x)}_(ik) that are usedin performing other improvements described below. Those improvementsresult in the channel output value signals being normalized moreeffectively. The improved normalization enhances the quality of theimage 78 by avoiding reductions in contrast between the pixels 84arising from effects other than actual differences in brightnesstemperature between corresponding points 16 of the scene 14.

A previously known millimeter wave image composition technique hasrecognized the fact that each channel has different responsecharacteristics. The previously known technique has attempted to scaleor normalize the output value signals from the channels in relation tothe differences in gain or amplification of each of the channels. Whilethis previously known normalization technique has been partiallyeffective, it has not been completely accurate because it has failed totake into account certain factors which are important for good contrastin millimeter wave imaging. For example, the previously known techniquehas assumed that each channel encounters the same mean scene brightnesstemperature. In reality, each channel scans only a portion of the scene,as shown by FIG. 4, and therefore each channel does not encounter thesame mean scene brightness temperature because each channel does notscan the entire scene 14. Using the same mean scene brightnesstemperature as a basis for normalizing the response characteristics ofall of the channels cannot achieve complete and accurate normalizationbecause the normalizing factor does not apply equally to the responsecharacteristics of each channel. The implication of this simplifyingassumption in previously known normalizing techniques is that there hasbeen non-optimal accounting for the drift in offset values of eachchannel over time. The offset value refers to a characteristic outputvalue signal level of each channel in response to a known input signal.The output value signal level from each channel will be slightlydifferent in magnitude in response to a known uniform input signalapplied to all of the channels. Lastly, despite recognizing thatindividual channel gain may be a basis for normalization, the previouslyknown normalizing technique failed to fully compensate for all thefactors which may influence inter-channel differences in gain as isdescribed below.

The previously known normalizing technique relates the voltage u_(i) ofthe output values signal 70 from the channel i (26) to the gain of thechannel g_(i), the scene brightness temperature s_(i), the channelreceiver noise temperature T^(R) _(i), and the offset voltage u_(o,i) asfollows in Equation (3):u _(i)=g _(i)(s _(i)+T ^(R) _(i))+u _(o,i),   (3)

Equation (3) is true only as long as a random noise portion of theoutput value signal from the channel is neglected. The more preciseequation for u_(i); must include a noise voltage term y_(i), in theright hand side of Equation (3), where y_(i), is a random variable withmean zero and standard deviation denoted by σ_(i). Neglecting the noiseterm y_(i), is acceptable for known prior art conclusions aboutcounteracting the effect of the drift in channel gain, and aboutremoving the dependence on channel offset. However, a problem occurswhen the above incomplete Equation (3) is implicitly used to develop anexpression for the variance (σ^(v) _(i))² of the output value signals ofthe channels i when viewing a scene containing a brightness temperaturedistribution with variance (σ^(s))². The problem is represented by thefollowing erroneous Equation (4):(σ^(v) _(i))²=g ² _(i)(σ^(s))²   (4)

Equation (4) implies that the standard deviation of the channel outputwhen viewing a scene with non-zero contrast is linearly proportional tothe gain of the channel, and this leads to using σ^(v) _(i) to normalizethe inter-channel difference in gains.

However, were the noise term y_(i) taken into account, the correctexpression for the channel output variance would be shown by thefollowing Equation (5):(σ^(v) _(i))²=g ² _(i)(σ^(s))² +(σ_(i))²   (5)

Since each channel has a thermal noise characteristic and someuncorrelated “backend” noise of standard deviation σ^(Backend), anexpression for the noise variance σ_(i) in terms of the gain of thechannel g_(i), the channel receiver noise temperature T^(R) _(i),thepre-detection bandwidth β and the time constant associated with thepost-detection bandwidth τ, and σ^(Backend) can be written as follows inEquation (6): $\begin{matrix}{\left( \sigma_{i} \right)^{2} = {\left( \frac{g_{i}T_{i}^{R}}{\sqrt{\beta\tau}} \right)^{2} + \left( \sigma^{Backend} \right)^{2}}} & (6)\end{matrix}$Backend noise results from the slight differences that arise fromquantizing analogue values into digital values, and environmental noisefrom other adjacent electrical components.

Equation (6) permits the standard deviation of the output value signalsof the channels to be written as shown in Equation (7): $\begin{matrix}{\sigma_{i}^{V} = \sqrt{{g_{i}^{2}\left\lbrack {\left( \sigma^{S} \right)^{2} + \frac{\left( T_{i}^{R} \right)^{2}}{\beta\tau}} \right\rbrack} + \left( \sigma^{Backend} \right)^{2}}} & (7)\end{matrix}$

Equation (7) reveals the impact of neglecting to consider the noisestandard deviation in using σ^(v) _(i) to scale the channel outputs.Consider a channel with such low gain g_(i) that its σ^(v) _(i) value ismore or less equal to the backend noise standard deviation σ^(Backend).After multiplication by the reciprocal of σ^(v) _(i) (i.e. the scalingoperation proposed in the known prior art), the output value signals ofthat channel would dominate over other channels with appreciable gain(and, therefore, higher channel standard deviation). Thus, the summationof values from different channels during image composition canpotentially create anomalous effects in the image corresponding toundesirable domination of the pixels along the scanning path trajectoryof extremely low gain channels.

Even if the σ^(Backend) related issue were not present, the channelreceiver noise temperature T^(R) _(i) that appears in the thermal noiseof the channel varies from channel to channel, and is independent ofchannel gain g_(i). This implies that only under the additional specialcondition of the same value of T^(R) _(i) for all channels would theprior art normalizing technique work as intended. In reality the channelnoise temperatures vary significantly from one channel to the other,despite efforts to thermally stabilize each of the channels.

To avoid these deficiencies in prior art normalizing techniques, σ^(v)_(i) is not used to compensate the inter-channel differences in gain.Instead, the present invention relies on the results of hot and coldload calibration experiments to determine channels gains. Experience hasshown the gain to be stable enough for long periods of time to scale thegain of the channel outputs.

The improvements in normalization also forego the assumption that everychannel in the focal plane array encounters the same mean scenebrightness temperature during a complete scan of the scene 14. Whilethis improves the degree of normalization and the degree of contrast andquality of the image produced, it becomes necessary to develop an entireset of mean scan brightness temperatures, one mean scan brightnesstemperature for each channel 26. The technique employed involvesestimating the mean scan brightness temperature for each channel. To doso it is necessary to provide a mathematical specification of the imageformation process.

The mathematical expressions for the image intensity value I(m) of agiven pixel m are statements of the result of combining or addingsignals related to and derived from the channel output value signals 70(FIG. 3) made during one complete scan. The mathematical expressions arein terms of normalized observations, obtained from the channel outputvalue signals 70 obtained by applying a normalizing or flat fieldingtechnique, either the prior art technique described previously, or theimproved technique constituting part of the present applicationdescribed below.

If every channel 26 in the focal plane array 24 had the same noiseresponse characteristics, which is not the case, the normalized outputvalue signals 70 could be obtained from the different channels withoutfirst weighting or adjusting them in any manner. Such a circumstancewould result in the following Equation (8) for the image intensity I(m)at pixel m: $\begin{matrix}{{I(m)} = {\frac{\sum\limits_{j = 1}^{N}\quad{\sum\limits_{l = 1}^{L}\quad{\delta_{jlm}{\hat{x}}_{jl}}}}{\sum\limits_{j = 1}^{N}\quad{\sum\limits_{l = 1}^{L}\quad\delta_{jlm}}}{\left( {1 \leq m \leq M} \right).}}} & (8)\end{matrix}$

However, the different channels have different noise temperatures anddifferent offsets, and therefore, different noise standard deviations,even after normalizing by the gain of the channel. Greater weight shouldbe given to the channels that are less noisy in composing the image 78.The best weight to apply to the contribution from channel j is inverselyproportional to the noise standard deviation, {circumflex over (σ)}_(j),of the normalized samples or observations. This follows from the wellknown principle that when forming the weighted sum of two or more randomvariables which have the same means but different variances, thevariance of the sum is minimized when the weighting is inverselyproportional to the standard deviation of the individual variables. Theapplication of this principle yields the following Equation (9) for thefinal image intensity of each pixel: $\begin{matrix}{{{I(m)} = \frac{\sum\limits_{j = 1}^{N}\quad{\sum\limits_{l = 1}^{L}\quad{\delta_{jlm}\frac{{\hat{x}}_{jl}}{{\hat{\sigma}}_{j}}}}}{\sum\limits_{j = 1}^{N}\quad{\sum\limits_{l = 1}^{L}\quad\frac{\delta_{jlm}}{{\hat{\sigma}}_{j}}}}},{1 \leq m \leq {M.}}} & (9)\end{matrix}$The image intensity I(m) is the estimate of the relative brightnesstemperature of the point 16 in the scene 14 represented by the pixel m.With the notation and image intensity Equation (9), the improved flatfielding or normalizing can be described.

The improved flat fielding technique involves calculating the mean scantemperatures for each channel, θ₁, θ₂, . . . , θ_(N) by setting up asystem of N simultaneous linear equations expressing relationshipsbetween the N unknowns θ₁, θ₂, . . . , θ_(N). The solution to thesesimultaneous linear equations yields the values of θ₁, θ₂, . . . , θ_(N)that permit computation of the improved flat fielded image intensities.

The normalized samples or observations {circumflex over (x)}_(ik) fromeach channel i (26) are expressed in terms of the output value signals(70) x_(ik) and the unknown θ_(i) in the following Equation (10):$\begin{matrix}{{{\hat{x}}_{ik} = {\frac{x_{ik} - {\overset{\_}{x}}_{i}}{g_{i}} + \theta_{i}}},{1 \leq i \leq N},{1 \leq k \leq {L.}}} & (10)\end{matrix}$

For the normalization represented in Equation (10), the associated noisestandard deviation {circumflex over (σ)}_(i), is related to the rawstandard deviation σ_(i) in the following Equation (11): $\begin{matrix}{{\hat{\sigma}}_{i} = {{\frac{\sigma_{i}}{g_{i}}1} \leq i \leq {N.}}} & (11)\end{matrix}$

Substituting in the preceding two Equations (10) and (11), in theexpression for the image intensity given in Equation (9), results in thefollowing Equation (12): $\begin{matrix}{{{I(m)} = \frac{\sum\limits_{j = 1}^{N}\quad{\sum\limits_{l = 1}^{L}\quad{{\delta_{jlm}\left( {\frac{x_{jl} - {\overset{\_}{x}}_{j}}{g_{j}} + \theta_{j}} \right)}\frac{g_{j}}{\sigma_{j}}}}}{\sum\limits_{j = 1}^{N}\quad{\sum\limits_{l = 1}^{L}\quad{\delta_{jlm}\frac{g_{j}}{\sigma_{j}}}}}},{1 \leq m \leq {M.}}} & (12)\end{matrix}$

θ₁, θ₂ , . . . , θ_(N) in Equation (12) are, as yet, unknown. Thecorrect image intensities I(m) are also unknown. However, Equation (12)makes explicit the dependence of the image intensities on the unknownθ₁, θ₂, . . . , θ_(N) and leads to the central concept of the improvedflat fielding technique: For each channel, impose the consistencycondition that the unknown mean scan temperature encountered by eachchannel be equal to the average of the intensities of those image pixelswhich that channel contributes to, relying, for the calculation of theimage intensities average, on the expression for the intensities interms of the unknown mean scan temperatures.

These consistency requirements provide a way of deriving as manysimultaneous linear equations as the number of unknowns. Consider thecircular path or trajectory of the energy scanned into any channel as ittraverses the scene 14 during a scan. An expression for the mean of thebrightness temperatures along this path is expressed in terms of theI(m) values along the path. For channel i, this expression is set forthin Equation (13) as follows: $\begin{matrix}{{{Mean}\quad{brightness}\quad{of}\quad{path}\quad{from}\quad{image}} = {\frac{\sum\limits_{k = 1}^{L}\quad{\sum\limits_{m = 1}^{M}\quad{\delta_{ikm}{I(m)}}}}{\sum\limits_{k = 1}^{L}\quad{\sum\limits_{m = 1}^{M}\quad\delta_{ikm}}} = {\frac{1}{L}{\sum\limits_{k = 1}^{L}\quad{\sum\limits_{m = 1}^{M}\quad{\delta_{ikm}{I(m)}}}}}}} & (13)\end{matrix}$

Equation (13) makes use of the fact that the denominator in the middleexpression sums to L. The requirement is next imposed that this meanscan brightness temperature, which is a function of all the channel meanbrightness temperatures, be equal to θ_(i), the mean scan brightnesstemperature encountered by the particular channel whose trajectory wastraversed in computing the above path mean. This strategy yields oneequation per channel for each of the N channels in the focal planearray, as shown in Equation (14): $\begin{matrix}\begin{matrix}{{{\frac{1}{L}{\sum\limits_{k = 1}^{L}{\sum\limits_{m = 1}^{M}{\delta_{ikm}{I(m)}}}}} = \theta_{i}},} & \quad & {1 \leq i \leq {N.}}\end{matrix} & (14)\end{matrix}$

Substituting in Equation (14), the expression for I(m) given in Equation(12) obtains the following linear system of equations (Equations (15))defining the unknown per channel mean relative brightness temperatures:$\begin{matrix}{{{{\frac{1}{L}{\sum\limits_{k = 1}^{L}{\sum\limits_{m = 1}^{M}{\delta_{ikm}\frac{\sum\limits_{j = 1}^{N}{\sum\limits_{l = 1}^{L}{\delta_{jlm}\frac{g_{j}}{\sigma_{j}}\theta_{j}}}}{\sum\limits_{j = 1}^{N}{\sum\limits_{l = 1}^{L}{\delta_{jlm}\frac{g_{j}}{\sigma_{j}}}}}}}}} - {L\quad\theta_{i}}} = {- {\sum\limits_{k = l}^{L}{\sum\limits_{m = 1}^{M}{\delta_{ikm}\frac{\sum\limits_{j = 1}^{N}{\sum\limits_{l = 1}^{L}{\delta_{jlm}\left( \frac{x_{jl} - {\overset{\_}{x}}_{j}}{\delta_{j}} \right)}}}{\sum\limits_{j = 1}^{N}{\sum\limits_{l = 1}^{L}{\delta_{jlm}\left( \frac{g_{j}}{\sigma_{j}} \right)}}}}}}}},{1 \leq i \leq {N.}}} & (15)\end{matrix}$

It is useful to write Equation (15) using matrix notation as follows inEquation (16): $\begin{matrix}{{A\quad\begin{bmatrix}\theta_{1} \\\vdots \\\theta_{N}\end{bmatrix}} = {b.}} & (16)\end{matrix}$

In Equation (16), A on the left hand side, is an N×N matrix ofcoefficients, and b on the right hand side is an N×1 column vector. Eachof the rows of A sum to zero, making A a singular matrix. This isconsistent with the fact that the mean scan brightness temperatures arerelative, permitting them to be estimated only up to an arbitraryadditive term. So, with no loss of generality, one of the θ₁, θ₂, . . ., θ_(N) can be set to an arbitrary value. It is convenient to set θ_(N)to zero. This permits rewriting the left hand side of Equation (16) asfollows: $\begin{matrix}\begin{matrix}{{A\begin{bmatrix}\theta_{1} \\\vdots \\\theta_{N - 1} \\0\end{bmatrix}} = {\underset{\underset{{its}\quad{Columns}\quad A_{1}\quad{through}\quad A_{N}}{{Matrix}\quad A\quad{expressed}\quad{in}\quad{terms}\quad{of}}}{\quad\underset{︸}{\begin{bmatrix}A_{1} & \cdots & A_{N - 1} & A_{N}\end{bmatrix}}\quad}\quad\begin{bmatrix}\theta_{1} \\\vdots \\\theta_{N - 1} \\0\end{bmatrix}}} \\{= {\underset{{Matrix}\quad{of}\quad{Size}\quad N \times {({N - 1})}}{\quad\underset{︸}{\begin{bmatrix}A_{1} & \cdots & A_{N - 1}\end{bmatrix}}\quad}\quad\begin{bmatrix}\theta_{1} \\\vdots \\\theta_{N - 1}\end{bmatrix}}} \\{= {A^{\prime}\quad\begin{bmatrix}\theta_{1} \\\vdots \\\theta_{N - 1}\end{bmatrix}}}\end{matrix} & (17)\end{matrix}$In Equation (17) A′ has been introduced to denote the N×(N−1) matrixthat results from deleting the N−th column vector of matrix A. Thus, thesystem of equations to be solved is the following Equation (18):$\begin{matrix}{{A^{\prime}\begin{bmatrix}\theta_{1} \\\vdots \\\theta_{N - 1} \\0\end{bmatrix}} = {b.}} & (18)\end{matrix}$

The positing of the consistency conditions among the various per channelmean scan brightness temperatures and the subsequent derivation of thelinear system given in Equation (18) is implemented to achieve improvednormalization or flat fielding. The actual solution of the equations iscarried out using a conventional computational method of solving linearsystems. Nevertheless, there are a few important details that must beconsidered when computing the solution.

A comparison of the left hand sides Equations (15) and (18) reveals thatthe elements of the matrix of coefficients A′ are independent of thechannel output value signals (70). This enhances the speed at which thecomputations are executed. If this was not the case, it would benecessary to undertake the high computational burden of computing thepseudo-inverse of an N×(N−1) matrix each time the flat fieldingnormalizing factors were computed. Fortunately, this burden is reducedby performing an inversion of matrix A′ prior to performing thecomputations to obtain the flat fielding normalizing factors, storing inmemory the resulting pseudo-inverse (A′)_(inv), and using the stored(A′)_(inv), during the actual flat fielding operation. The singularvalue decomposition of A′ is used to calculate its pseudo-inverse,(A′)_(inv).

A comparison of the right hand sides of Equations (15) and (18) showsthat the elements of the column vector b depend on the channel outputvalue signals, and are sums of the intensities of an intermediate imageI′(m) that can be defined by the following Equation (19):$\begin{matrix}\begin{matrix}{{{I^{\prime}(m)} = \frac{\sum\limits_{j = 1}^{N}{\sum\limits_{l = 1}^{L}{\delta_{jlm}\left( \frac{x_{jl} - {\overset{\_}{x}}_{j}}{\sigma_{j}} \right)}}}{\sum\limits_{j = 1}^{N}{\sum\limits_{l = 1}^{L}{\delta_{jlm}\frac{g_{j}}{\sigma_{j}}}}}},} & \quad & {1 \leq m \leq {M.}}\end{matrix} & (19)\end{matrix}$It is convenient to compute and temporarily store I′(m) beforeproceeding to the estimation of θ_(i), θ₂, . . . , θ_(N).

The right hand side column vector b of Equation (18) is calculated anewat each scan to obtain the estimates of the channel mean scantemperatures. The θ₁, θ₂, . . . , θ_(N) are obtained by post-multiplyingthe stored pseudo-inverse of matrix A′, i.e. (A′)_(inv), by the mostrecently formed b as shown in the following Equation (20):$\begin{matrix}\begin{matrix}{{\begin{bmatrix}\theta_{1} \\\vdots \\\theta_{N - 1}\end{bmatrix} = {\underset{{Precomputed}\quad{pseudo}\text{-}{inverse}}{\quad\underset{︸}{\left( A^{\prime} \right)_{inv}}\quad} \cdot b}},} \\\begin{matrix}{{And},{{of}\quad{course}},} & {\theta_{N} = 0.}\end{matrix}\end{matrix} & (20)\end{matrix}$

The estimated θ₁, θ₂, . . . , θ_(N) are then used to update theintermediate image I′(m) to obtain the final flat fielded image I(m),1≦m≦M, that is described by Equation (12).

It has been discovered that even when using the normalized channeloutput value signals, anomalous effects appear in the image 78. Theanomalous effects result from differences in channel noisecharacteristics, which can not be predicted or calculated. Nevertheless,the present improvements further enhance the quality of the image 78.These improvements are better understood by reference to an imagecomposition technique employing only direct summation of the normalizedchannel output value signals, as described below in Algorithm 1.

The image 78 is derived from the output value signals 70 of theindividual channels 26 at the end of each scan of the scene. In thesimple but unrealistic situation where all the channels of the focalplane array had the same gain, offset, and noise temperature, the imagecomposition would be accomplished by summing the output values signals70 as contributions to each image pixel, and normalizing each sum by thenumber of contributions received. Assuming the channels are sampled ateach discrete position of the wedge shaped element 40, the inputs intothis computation are the L number of subframes, with each subframecontaining N number of channel output value signals 70 (each anobservation), and the measured position of the wedge shaped element 40represented by the position signals 80. The channel observations orsamples are denoted by with the first subscript, i, specifying thechannel number and the second subscript, k, the position of the wedgeshaped element. (1≦i≦N, 1≦k≦L). A precomputed table of pixel positionsis exemplified by the table set forth above.

In a radiometer based millimeter wave imaging camera, the followingAlgorithm 1 is applied to compose the complete image 78, whose intensityat each pixel m is denoted by I(m): Algorithm 1: Basic Unweighted ImageComposition 1. Compute the pixel position table. 2. Initialize the imagedisplay I(m) to zero for 1 ≦ m ≦ M. 3. Initialize an array ofcontribution counts C(m) to zero for 1 ≦ m ≦ M. 4. For each position kbetween 1 through L of the wedge shaped element, and for thecontribution from each channel number i between 1 through N, Look up thepixel number m corresponding to position k and channel ifrom theprecomputed pixel position table. I(m) = I(m) + x_(ik). C(m) = C(m) + 1.5. For each m between I and M, ${I(m)} = \frac{I(m)}{C(m)}$

If each channel of the focal plane array had the same noisecharacteristics and their different gains and offsets had beennormalized, Algorithm 1 could be used to compose the image 78, using themodified channel observations {circumflex over (x)}_(ik) obtained fromthe original channel observations x_(ik) by using flat fielding.However, each channel does not have the same noise characteristics.Therefore, even after the output value signals of each channel have beennormalized to account for gain and offset differences, preferably usingthe improved flat fielding technique described above, the channels arelikely to still differ in their noise characteristics. This is confirmedby noise measurement experiments and direct measurements of the standarddeviations of noise from each of the channels.

The improved aspect of the present invention is to give greater weightto those output value signals 70 from channels 26 of the focal planearray 24 which are less noisy compared to the output value signals 70from channels 26 which are more noisy, as discussed above in conjunctionwith Equation (9). The best weight to apply to the contribution fromchannel i is inversely proportional to the noise standard deviation,{circumflex over (σ)}_(i), of the normalized channel observations. Thisfollows from the well known principle that when forming the weighted sumof two or more random variables which have the same means but differentstandard deviations, the standard deviation of the sum is minimized whenthe weighting is inversely proportional to the standard deviation of theindividual variables.

Employing this weighting concept in composing the millimeter wave image78 involves calculating a weighted summation of the normalized channelobservations. The weight to be given to the normalized channelobservations is the reciprocal of the normalized noise standarddeviation 1/{circumflex over (σ)}_(i) , for 1≦i≦N. So, the improvementin the image composition algorithm requires an additional set of inputs(the weights) to be applied to the normalized observations {circumflexover (x)} _(ik) , as set forth in the following Algorithm 2: Algorithm2: Channel Weighting Based Image Composition 1. Compute the pixelposition table. Measure the channel noise standard deviations. 2.Initialize the image array I(m) to zero for 1 ≦ m ≦ M. 3. Initialize anarray of contribution counts C(m) to zero for 1 ≦ m ≦ M. 4. For eachwedge position k between 1 through L, and for each channel number ibetween 1 through N, Look up the pixel number m corresponding to wedgeposition k and channel i from the precomputed position table.$\begin{matrix}{{I(m)} = {{I(m)} + {\frac{{\hat{x}}_{ik}}{{\hat{\sigma}}_{i}}.}}} \\{{C(m)} = {{C(m)} + {\frac{1}{{\hat{\sigma}}_{i}}.}}}\end{matrix}\quad$ 5. For each m between 1 and M,${I(m)} = \frac{I(m)}{C(m)}$

Mathematically, the image composed by use of the direct summationalgorithm, Algorithm 1 set forth above, can be expressed by Equation(8). Specifying the δ_(ikm) in Equation (8) is equivalent to specifyingthe scanning pattern in the form exemplified above in the pixel positiontable. Thus, δ_(ikm) can be precomputed for 1≦i≦N, 1 ≦k≦L, and 1≦m≦M.

In contrast to Equation (8), the result of using the weighted summationimage composition algorithm, Algorithm 2 set forth above, can bemathematically expressed in Equation (9).

The weighted summation image composition Equation (9), leads to thesuppression and substantial elimination of undesired anomalous effectscreated by excessively noisy channels.

After having eliminated the effects of baseline signals, and upon usingthe flat fielding technique for channel normalization based on gainmeasurements obtained by hot and cold load calibration experiments, andupon weighting the contributions of each channel in the summation of thevalues for each pixel of the image in such a way that the contributionsfrom the more noisy channels are diminished while the contributions fromthe less noisy channels are enhanced, the improved composition of theimage 78 may proceed according to Algorithm 3 described below. Algorithm3 illustrates the sequence of carrying out the steps of image formationin a radiometer based millimeter wave imaging camera. Algorithm 3incorporates baseline subtraction, flat field normalizing, and channelweighting as described above. Algorithm 3: Image Formation with BaselineSubtraction, Channel Weighting and Flat Fielding 1. Compute channelstandard deviations σ_(i), channel gains g_(i), and the matrix(A′)_(inv) from calibration experiments channel observations. Computethe pixel position table. Compute the baseline signal B_(ik), 1 ≦ i ≦ N,1 ≦ k ≦ L. 2. Initialize the image array I(m) to zero for 1 ≦ m ≦ M. 3.Initialize an array of contribution counts C(m) to zero for 1 ≦ m ≦ M.4. Subtract the baseline: For each wedge position k between 1 through L,For each channel number i between 1 through N, x_(ik) = u_(ik) − B_(ik).5. For each channel number i between 1 through N,${{Compute}\quad{the}\quad{channel}\quad{mean}\text{:}\quad{\overset{\_}{x}}_{ik}} = {\sum\limits_{k = 1}^{L}{x_{ik}.}}$6. For each wedge position k between 1 through L, For each channelnumber i between 1 through N, Look up the pixel number m correspondingto wedge position k and channel i from the precomputed position table.${\begin{matrix}{{I(m)} = {{I(m)} + {\frac{x_{ik} - {\overset{\_}{x}}_{i}}{{\hat{\sigma}}_{i}}.}}} \\{{C(m)} = {{C(m)} + {\frac{g_{i}}{{\hat{\sigma}}_{i}}.}}}\end{matrix}\quad}\quad$ 7. For each channel number i between 1 throughN, b_(i) = 0 For each wedge position k between 1 through L, Look up thepixel number m corresponding to wedge position k and channel i from theprecomputed position table. $b_{i} = {b_{i} - {\frac{I(m)}{C(m)}.}}$ 8.Compute the vector of channel-wise mean scan temperatures${\begin{bmatrix}\theta_{1} \\\vdots \\\theta_{N - 1}\end{bmatrix} = {\left( A^{\prime} \right)_{inv} \cdot \begin{bmatrix}b_{1} \\\vdots \\b_{N}\end{bmatrix}}},{{{and}\quad\theta_{N}} = 0},$ 9. For each wedgeposition k between 1 through L, For each channel number i between 1through N, Look up the pixel number m corresponding to wedge position kand channel ifrom the precomputed position table.${I(m)} = {{I(m)} + {\frac{g_{i}}{\sigma_{i}}{\theta_{i}.}}}$ 10. Foreach m between I and M, ${I(m)} = \frac{I(m)}{C(m)}$

The flowchart shown in FIG. 6 describes a process flow 100 of actions,information and computations involved in obtaining and computing theenhanced image 78 using the improvements described above. A conventionemployed in the flowchart 100 is that those boxes having straight andperpendicular sides represent a computation, those boxes having slantedand non-perpendicular vertical sides represent data that is used once,and those boxes having curved vertical sides represent data that is usedrepeatedly, i.e. persistent data.

The process flow 100 begins at 102 where observations from several scansover two scenes of uniform brightness are collected. One of the twoscenes of uniform brightness may be the background within an enclosurewhich has been air-conditioned to achieve a uniform temperaturethroughout. The second one of the two scenes of uniform brightness maybe established by a black object inserted in the optical path 28.Scanning two scenes of different brightness temperatures establishes twodifferent output value signals from each channel, and these two outputvalue signals are used in calculating the gain of each channel. Inaddition or simultaneously at 103, further observations from scanning ascene of uniform brightness are also collected to establish a curve ofthe baseline signal described above.

The data obtained from the two scanning steps at 102 and 103 providesthe necessary information needed to make the calibration calculations at104, to calculate the standard deviations of the channel output valuesignals at 108, and to compute the baseline signal curves at 109. Thecalibrations at 104 result in establishing the values of the channelgains at 106. The standard deviations calculated at 108 proceed inaccordance with conventional standard deviation calculation techniquesand result in the standard deviation values for each channel at 110. Thecomputation of the baseline at 109 results in the baseline curveinformation for each channel at 111.

At 112, the scanning paths or trajectories of each of the channels isobtained and correlated to the pixels 84 of the display 86 in the mannerdescribed above. Preferably, step 112 is accomplished by populating andusing the pixel position look-up table described above which correlatesthe rotational position of the wedge shaped element 40 and the points 16in the scene 14 and the pixels 84 in the image 78 (FIG. 1).

At 114, the matrix A′ is calculated in the manner described above withrespect to Equation (18), and the value of the matrix A′ is establishedat 116. The pseudo-inverse of (A′)_(inv), is next computed at 118,preferably by using singular value decomposition as described above, andthe pseudo-inverse result is stored at 120.

The steps 102-120 of the process flow 100 described above may beexecuted once and the data resulting from the computations thereafterstored for use repeatedly over a relatively large number of subsequentscans when imaging the scene 14. While it may not be necessary to do so,it may be advisable to repeat the initialization steps 102-120periodically during the use of the millimeter wave imaging camera 10.The initialization steps 102-120 should be performed only after theelements of the millimeter wave imaging camera have warmed up andreached thermal equilibrium in an environment where use of the camera islikely to be continued, so the results from the steps will have themaximum value and accuracy.

The remaining steps 122-138 of the process flow 100 are performed duringeach scan to create a single image. Each time the image is updated, thesteps 122-138 are preferably again performed. In this manner, the flatfield normalizing factors obtained in accordance with the presentinvention will be applied to each image and each update of that image atthe time that the image is created and updated. Consequently, effects ofdrift in the offset value will be immediately and effectively normalizedand compensated with each scan.

At 122, the output value signals 70 or samples from a scan of the entirescene are collected as described above. At 121, the baseline values 111are subtracted from the output value signals 70, resulting in thecreation of baseline subtracted samples 123.

Using the baseline subtracted samples 123, the intermediate image I′ isformed at 125 by applying the Equation (19), and the weightingcontributions C are obtained by applying step 6 of Algorithm 3. Theresult of the computation at 125 is the value of the intermediate imageI′ and, weighting contributions C at 127.

The value of the intermediate image I′ and the weighting C contributionsestablished at 127 are used along with the information at 112 describingthe scanning paths or trajectories of the channels in a computation ofthe vector b at 128. The computation at 128 occurs in accordance withEquations (15) and (16), and the value of the vector b is established at130.

At 132, the stored pseudo-inverse of the matrix obtained from 120 ispost-multiplied by the value of the vector b, obtained at 130. Thecomputation at 132 results in the estimated values of the mean scantemperatures for each channel at 134. At 136, the final image l iscomputed using the mean scan temperatures obtained at 134, and the finalflat fielded image is produced at 138.

The production of the final image at 138 obtains the numerousimprovements described, thereby resulting in the creation of an image 78having more contrast and resolution, or in the creation of an imagehaving adequate contrast and resolution from radiated energy signalswith less brightness temperature contrast. By performing the baselinesubtraction before using the camera for imaging, and by performing theflat fielding and channel weighting with each scan 122, an improvedimage results under circumstances where the response characteristics ofthe channels can not otherwise be improved. Many other improvements andadvantages will be apparent upon gaining a complete understanding of thepresent invention.

A presently preferred embodiment of the present invention and many ofits improvements have been described with a degree of particularity.This description is a preferred example of implementing the invention,and is not necessarily intended to limit the scope of the invention. Thescope of the invention is defined by the following claims.

1-26. (canceled)
 27. A millimeter wave imaging method to compensate forvariation in response to noise in at least one output signal from atleast one channel, the method comprising: weighting at least onecomposition signal by a first weighting factor; and weighting at leastone weighted composition signal by a second weighting factor.
 28. Themethod of claim 27, wherein the noise is from at least one output signalof at least one channel.
 29. The method of claim 28, wherein eachweighted composition signal is related to an output signal.
 30. Themethod of claim 28, wherein each output signal is from a channel andeach channel scans radiant energy emanating from a scene.
 31. The methodof claim 27, further comprising: establishing a standard deviation ofvariation of at least one output signal relative to a mean of outputsignals; and creating at least one weighted composition signal bymultiplying the at least one output signal by a reciprocal of thestandard deviation corresponding to the at least one output signal. 32.The method of claim 31, further comprising: composing an image by addingeach weighted composition signal.
 33. The method of claim 28, furthercomprising: measuring the variation of the at least one output signalfrom a channel to establish the weighting factor for the channel inresponse to radiant energy from a scene of uniform brightness.
 34. Themethod of claim 30, further comprising: composing an image with aplurality of pixels, each pixel corresponding to a point in the scene;directing radiant energy emanating from each point in the scene intodifferent channels; and composing an intensity of each pixel of theimage from the weighted composition signals from each channel into whichthe radiant energy emanating from the corresponding point in the sceneis directed.
 35. The method of claim 34, further comprising: composingthe intensity of each pixel by adding each weighted composition signalobtained from corresponding output signals.
 36. The method of claim 35,further comprising: composing the intensity of each pixel from eachweighted composition signal obtained from only the corresponding outputsignals of the channels into which the radiant energy emanating from thepoint in the scene corresponding to the pixel was directed.
 37. Themethod of claim 36, further comprising: establishing a standarddeviation for at least one output signal of each channel that derivesthe radiant energy emanating from the corresponding point relative to amean of output signals; and creating at least one weighted compositionsignal for composing the intensity of each pixel by multiplying the atleast one output signal by a reciprocal of the standard deviationcorresponding to the at least one output signal.
 38. The method of claim35, further comprising: periodically updating the image created byobtaining new output signals from each channel; and creating eachupdated image from each weighted composition signal using weightingfactors derived prior to updating the image.
 39. The method of claim 35,further comprising: measuring the variation of the at least one outputsignal from a channel to establish the weighting factor for the channelin response to radiant energy from a scene of uniform brightness. 40.The method of claim 35, further comprising: directing the radiant energyemanating from each point in the scene to each channel with a movablescanning element.
 41. The method of claim 35, further comprising:obtaining a magnitude of baseline signal components of each outputsignal from each channel at each position of a movable scanning element;and subtracting the magnitude of baseline signal components at eachposition of the movable scanning element from an output signal of achannel derived from the radiant energy directed into the channel from ascene of non-uniform brightness at corresponding positions of themovable scanning element.
 42. The method of claim 41, furthercomprising: measuring the magnitude of the baseline signal at eachposition from which radiant energy is directed into the channel from ascene of uniform brightness.
 43. The method of claim 41, furthercomprising: composing an intensity of each pixel from at least onebaseline-compensated composition signal formed by subtracting thebaseline signal from the output signal.
 44. The method of claim 43,further comprising: composing the intensity of each pixel by weightingeach baseline-compensated composition signal by a weighting factorestablished from variations in the corresponding output signals of thechannel from which the corresponding output signals were obtained. 45.The method of claim 44, further comprising: composing the intensity ofeach pixel of the image by adding each weighted baseline-compensatedcomposition signal from each channel into which the radiant energyemanating from the corresponding point in the scene is directed.
 46. Themethod of claim 45, further comprising: using as the weighting factorthe reciprocal of the standard deviation of at least one output signal.47. The method of claim 43, further comprising: normalizing eachweighted baseline-compensated composition signal from each channel onthe basis of a flat fielding response of the channels.
 48. The method ofclaim 47, further comprising: normalizing each weightedbaseline-compensated composition signal from each channel by anormalizing factor which is related to a gain of each channel and adrift in offset of each output signal from each channel.
 49. The methodof claim 48, further comprising: calculating the normalizing factor frominformation defining the individual gain and offset characteristics ofeach channel.
 50. The method of claim 49, further comprising:calculating the normalizing factor based on a consistency condition thatan unknown mean scan temperature encountered by each channel into whichradiant energy from a portion of the scene is scanned is equal to anaverage of the intensities of those pixels to which thebaseline-compensated composition signals contributes; and calculatingthe average of pixel intensities based on an expression for the averagepixel intensities in terms of the unknown mean scan temperature of eachchannel.
 51. The method of claim 48, further comprising: periodicallyupdating the image created by obtaining new output signals from eachchannel; creating each updated image from each normalized weightedbaseline-compensated composition signal; and calculating the normalizingfactor with each scan of the radiant energy from the entire scene intoeach channel.
 52. The method of claim 47, further comprising:normalizing each weighted baseline-compensated composition signal fromeach channel on the basis that each channel observes a different meanscan brightness temperature from the radiant energy scanned from aportion of the scene than the mean brightness temperature of the entirescene.
 53. A detector camera, comprising: a plurality of channelscapable of scanning radiant energy emanating from one or more points ina scene and each channel is capable of converting the radiant energyinto output signals; and a processor capable of compensating forvariation in response to noise in the output signals, weighting at leastone composition signals by a first weighting factor; and weighting atleast one weighted composition signal by a second weighting factor. 54.The camera of claim 53, wherein the plurality of channels receive theradiant energy from at least one of a movable scanning element and anoptical element.
 55. The camera of claim 53, wherein the processor formsoutput image signals on the basis of each weighted composition signalsand the camera further comprises: a display for providing an imageformed on the basis of the output image signals.
 56. The camera of claim53, wherein the plurality of channels includes a focal plane array ofchannels.
 57. The camera of claim 53, wherein the camera is utilized forone of passive imaging and active imaging.
 58. The camera of claim 57,wherein each channel includes a radiometer channel when the camera isutilized in passive imaging.
 59. The camera of claim 57, wherein eachchannel includes a receiver channel when the camera is utilized inactive imaging.
 60. The camera of claim 53, wherein each channelincludes an antenna.
 61. The camera of claim 60, wherein the antennaincludes an endfire traveling wave slot antenna.
 62. The camera of claim53, wherein the camera includes a movable scanning element in the formof a wedge shaped refractive element which rotates about an axis. 63.The camera of claim 53, wherein the camera includes a movable scanningelement in the form of a rotating mirror arranged in the optical pathand retained at a non-orthogonal angle to its rotational axis.
 64. Thecamera of claim 53, further comprising: a movable scanning element; anda position sensor connected to the movable scanning element, wherein theposition sensor provides position signals to the processor; wherein theposition signals correspond to positions of the movable scanning elementand wherein the processor uses the position signals for furtherdetermining the normalizing factor.
 65. A system, comprising: aprocessor; a plurality of channels; a computer-readable storing mediumstoring a set of instructions capable of being executed by the processorto implement a millimeter wave imaging method to compensate forvariation in response to noise in image signals and capable ofperforming the steps of: weighting at least one composition signal by afirst weighting factor; and weighting at least one weighted compositionsignal by a second weighting factor.
 66. A computer-readable storingmedium storing a set of instructions capable of being executed by aprocessor to implement a millimeter wave imaging method to compensatefor variation in response to noise in image signals and capable ofperforming the steps of: weighting at least one composition signal by afirst weighting factor; and weighting at least one weighted compositionsignal by a second weighting factor.